| Title | Description | |
|---|---|---|
| (I) | Import libraries | Import and Initialize python libraries. |
| (II) | Starfish | A shape made using curves in 'Matplotlib'. |
| (III) | 3d Scatter of Iris | Each point represents an iris flower with its position determined by its sepal length, sepal width, and petal width.. |
| (IV) | BiVariate Guasssian | A Gaussian Bivariate plotted using seaborn |
| (V) | Connect with me | Links to my GitHub and LinkedIn profiles |
import matplotlib.pyplot as plt
import numpy as np
import plotly.express as px
import plotly.graph_objects as go
import seaborn as sns
import plotly.io as pio
pio.renderers.default = 'notebook'
a = np.linspace(0, 2*np.pi, 100)
r1 = 0.5 + 0.5*np.sin(6*a)
r2 = 0.5 + 0.5*np.cos(6*a)
x1 = r1 * np.cos(a)
y1 = r1 * np.sin(a)
x2 = r2 * np.cos(a)
y2 = r2 * np.sin(a)
fig = plt.figure(facecolor='lightgrey')
plt.plot(x1, y1, 'y')
plt.plot(x2, y2, 'r')
plt.title('Starfish Shape')
Text(0.5, 1.0, 'Starfish Shape')
df = px.data.iris()
fig = px.scatter_3d(df, x='sepal_length', y='sepal_width', z='petal_width',
color='species')
fig.show()
sns.set_theme(style="darkgrid")
n = 10000
mean = [0, 0]
cov = [(2, .4), (.4, .2)]
rng = np.random.RandomState(1)
x, y = rng.multivariate_normal(mean, cov, n).T
f, ax = plt.subplots(figsize=(6, 6))
sns.scatterplot(x=x, y=y, s=5, color=".15")
sns.histplot(x=x, y=y, bins=50, pthresh=.1, cmap="mako")
sns.kdeplot(x=x, y=y, levels=5, color="w", linewidths=1)
<Axes: >
